Telephone call servicing centers that have interactive voice response systems (IVRS)(s) continue to improve by implementing new technologies. One such recent development is a speech recognition technology that supports a “natural language” type interaction between automated systems and customers. A natural language interaction allows a customer to speak naturally, and a voice recognition system can route a call or provide requested information responsive to the freely spoken dialect. A goal of an IVRS is to determine why a customer is calling a service center and to provide the customer with information, or route the customer to an appropriate agent or destination. Ensuring that a given IVRS is operating properly and accurately is often very difficult. An IVRS is typically comprised of multiple components that can operate at less than peak efficiency or even fail. One significant problem that occurs in IVRSs is that certain failures degrade system performance but do not cause total failure, wherein detection of such a failure is difficult. Call centers often service a huge volume of calls and even if a small percentage of calls are improperly serviced, the costs associated with such calls are significant. In addition, unsuccessful call servicing can result in caller dissatisfaction. Accordingly, there is a need for an improved method and system for tracking automated call center performance.